Java is one of the most widely used programming languages, and a key contributor to its success is VMware Tanzu’s Spring, the most common framework for Java development. The Spring Framework is built on top of the Java Virtual Machine and provides a consistent programming and configuration model for application developers. From inception, it was designed with developer experience and modularity in mind.

The open-source application framework has been accelerating Java development times since its inception in 2004 (Happy 20th birthday). Since then, the platform has been expanding: growing 50% year over year during the last five years. In this blog we’re exploring what makes Spring important to Java, how the framework influenced the developer experience, and a look at the latest version of Spring, which introduces features to support AI integration.

Spring Success

Two decades ago, there were dozens of different ways to connect to a database, something just about every application has to do at some point. “At the time, the various approaches were very cumbersome: developers wrote a lot of code and gained very little functionality,” explained Mark Pollack, a Senior Staff Engineer, Tanzu Division, Broadcom. “Spring provided a lot of value by simplifying the process. Just getting a single app to talk to a database, present a web form, and do transactions correctly was a huge win. In that era, developers could spend weeks trying to create that function.”

Another reason for its success is its enterprise-focus. Most open source projects concentrate on the consumer market. However, large companies invest a lot of money building applications to run their businesses. “At the end of the day, large corporations’ largest expense is probably their developers,” explained Ryan Morgan, Senior Director of Engineering, Tanzu Division, Broadcom. Spring makes developer teams more efficient, which greatly enhances the bottom line.

Through the years, the ecosystem has grown. “There’s a large and vibrant community behind Spring,” noted Tanzu’s Morgan. Now, it has more than 200 different technology starters. These software building blocks make it simpler for software engineers to integrate their code with different third-party systems.

Get a Great Start

Development problems evolve over time, so various elements were added. Spring Initializer is a bootstrapping tool, a way for developers to create a new project. “Normally, software engineers started from a blank piece of paper and had to figure out what type of project it was and what type of libraries were needed,” said Tanzu’s Morgan. Then, they searched the web to find some place in the documentation that told them what library dependency was needed to add for different pieces of functionality. Then invariably, you cut and pasted from something that wasn’t consistent. You ended up with a mess.”

With Spring Initializer, software engineers go to a website which has clear instructions about what the options are and presents them in a typical web form. Then, they enter the Generate command and out comes a shell that they can use to start building their program. The solution does not generate any code but solves the problem of finding the right application dependencies. Developers start faster and are less frustrated than previous methods.

Under development is Spring CLI, which not only creates the shell of the app but also includes code. The advances have a significant impact because 1 million new projects are created each month.

Meet the Need for Development Speed

The last 10 years have seen a major move to container deployment and Spring has aligned with this paradigm shift. “Really, when you think about all those cloud native patterns, a lot of those container functions are really baked into our projects already,” stated Tanzu’s Morgan. “If you want to do distributed configuration, we have a solution for that. You want to do service discovery; Spring has patterns and tools for that.”

Recently, a major change to Spring occurred. Rather than release new functions autonomously, they are gathered and bundled into Spring Boot. Version 3.0, which is based on Spring Framework 6.0, requires Java 17 or above. Previously, Spring supported Java 8, so the change is significant for some companies.

Better performance is one benefit from the change. “We’ve seen customers realize 15% performance improvements, just from doing the upgrade,” said Tanzu’s Morgan.

Java Supports Generative AI

AI is being woven into many applications, especially with the emergence of Generative AI solutions. They represent a quantum leap in capabilities and overall intelligence compared to previous iterations of AI. One reason why today’s generative models are gaining so much attention is that they work with much larger volumes of information (hundreds of billions of words) and larger data models (hundreds of billions of parameters) compared to previous AI systems. They possess impressive and unprecedented power. Consequently, they can perform very sophisticated functions.

However as developers try to take advantage of the functionality, platform diversity again presents development challenges. “OpenAI has their API, Amazon Bedrock offers a different one, and so do other companies,” noted Tanzu’s Pollack.

A guiding focus and design principle in the Spring framework is simplifying such work by providing common abstractions over similar technologies and interfaces. Spring AI is quickly becoming the starting point when Java developers write AI applications. “Spring AI has the common patterns that Spring developers are used to,” noted Tanzu’s Pollack. It can abstract out models, clients, etc. in ways that are familiar to Spring users.”

Another crucial part of AI applications is using a vector database. Spring supports multiple vector databases, and its portable API simplifies changing implementations. So, Spring streamlines AI application development.

Java has been a popular programming language for enterprises for decades. Spring provides software engineers with tools that help them enhance the development process. The framework has reached its 20th year of empowering developers, and its years, engaged community is laying the groundwork for continued expansion in the coming decades. “Maybe one reason why Spring continues to do well is it constantly tries to improve itself and doesn’t just rest on its laurels,” concluded Tanzu’s Pollack.

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Apache Iceberg is an open source high-performance format for huge data tables. Iceberg enables the use of SQL tables for big data, while making it possible for engines like Spark and Hive to safely work with the same tables, at the same time.

Iceberg was started at Netflix by Ryan Blue and Dan Weeks, and was open-sourced and donated to the Apache Software Foundation in November 2018. It has now been adopted at many other companies including Airbnb, Apple, and Lyft.

Ryan Blue joins the podcast to describe the origins of Iceberg, how it works, the problems it solves, collaborating with Apple and others to open-source it, and more.

This episode is hosted by Lee Atchison. Lee Atchison is a software architect, author, and thought leader on cloud computing and application modernization. His best-selling book, Architecting for Scale (O’Reilly Media), is an essential resource for technical teams looking to maintain high availability and manage risk in their cloud environments.

Lee is the host of his podcast, Modern Digital Business, an engaging and informative podcast produced for people looking to build and grow their digital business with the help of modern applications and processes developed for today’s fast-moving business environment. Listen at mdb.fm. Follow Lee at softwarearchitectureinsights.com, and see all his content at leeatchison.com.

Please click here to see the transcript of this episode.

Sponsorship inquiries: [email protected]

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Starburst is a data lake analytics platform. It’s designed to help users work with structured data at scale, and is built on the open source platform, Trino.

Adam Ferrari is the SVP of Engineering at Starburst. He joins the show to talk about Starburst, data engineering, and what it takes to build a data lake.

Full Disclosure: Starburst is a sponsor of Software Engineering Daily

Sean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from information visualization to quantum computing. Currently, Sean is Head of Marketing and Developer Relations at Skyflow and host of the podcast Partially Redacted, a podcast about privacy and security engineering. You can connect with Sean on Twitter @seanfalconer .

 

Please click here to see the transcript of this episode.

Watch the video episode here

Sponsorship inquiries: [email protected]

 

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Building scalable software applications can be complex and typically requires dozens of different tools. The engineering often involves handling many arcane tasks that are distant from actual application logic. In addition, a lack of a cohesive model for building applications can lead to substantial engineering costs.

Nathan Marz is the creator of Rama, which is a platform for building end-to-end, scalable backends. Previously Nathan led engineering at BackType which was acquired by Twitter in 2011. In addition, Nathan created the Apache Storm project and is the author of the book Big Data: Principles and best practices of scalable realtime data systems. Nathan joins the podcast today to talk about Rama, and how to build scalable software applications.

This episode is hosted by Lee Atchison. Lee Atchison is a software architect, author, and thought leader on cloud computing and application modernization. His best-selling book, Architecting for Scale (O’Reilly Media), is an essential resource for technical teams looking to maintain high availability and manage risk in their cloud environments.

Lee is the host of his podcast, Modern Digital Business, an engaging and informative podcast produced for people looking to build and grow their digital business with the help of modern applications and processes developed for today’s fast-moving business environment. Listen at mdb.fm. Follow Lee at softwarearchitectureinsights.com, and see all his content at leeatchison.com.

Please click here to see the transcript of this episode.

Sponsorship inquiries:[email protected]

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SurrealDB is the result of a long-time collaboration between brothers Tobie and Jaime Morgan Hitchcock. The project has modest origins and started merely to support other projects the brothers were working on. However, over time the project grew and in 2021  they started working on it full-time. Since then the project has gained serious adoption.

What’s makes SurrealDB so special? Tobie Morgan Hitchcock is the CEO of SurrealDB and he joins the show to talk about his multimodal database, support for graph and time series data, why they rewrote the entire project in Rust, and more.

Starting her career as a software developer, Jocelyn Houle is now a Senior Director of Product Management at Securiti.ai, a unified data protection and governance platform. Before that, she was an Operating Partner at Capital One Ventures investing in data and AI startups. Jocelyn has been a founder of two startups and a full life cycle, technical product manager at large companies like Fannie Mae, Microsoft and Capital One.  Follow Jocelyn on LinkedIn  or Twitter @jocelynbyrne.

Please click here to see the transcript of this episode.

Sponsorship inquiries:[email protected]

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Maritime logistics is the process organizing the movement of goods across the ocean. Historically, this has been a challenging problem because of the multinational nature of shipping, as well as piracy, smuggling, and legacy technology. It’s also profoundly important for security reasons, and because 90% of what we buy travels over the oceans. Ocean vessels produce a lot of CO2, which adds climate change and energy dimensions to maritime logistics.

Windward AI is a maritime logistics platform that was started 13 years ago by two ex-Israeli naval officers. The idea for the company came from the observation that, at that time, it was hard or impossible to know what’s happening on the deep sea.

Benny Keinan is the VP of R&D and Lior Resisi is the Data Platforms Group Lead at Windward AI. They join the podcast today to talk about the technical and practical challenges of maritime logistics, why Rockset was the right database for their unique datasets, the impact of the Ukraine war, and more.

This episode is hosted by Lee Atchison. Lee Atchison is a software architect, author, and thought leader on cloud computing and application modernization. His best-selling book,  Architecting for Scale (O’Reilly Media), is an essential resource for technical teams looking to maintain high availability and manage risk in their cloud environments.

Lee is the host of his podcast, Modern Digital Business, an engaging and informative podcast produced for people looking to build and grow their digital business with the help of modern applications and processes developed for today’s fast-moving business environment. Listen at mdb.fm. Follow Lee at softwarearchitectureinsights.com, and see all his content at leeatchison.com.

Please click here to see the transcript of this episode.

Sponsorship inquiries: [email protected]

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Data breaches at major companies are so now common that they hardly make the news. The Wikipedia page on data breaches lists over 350 between 2004 and 2023. The Equifax breach in 2017 was especially notable because over 160 million records were leaked, and much of the data was acquired by Equifax without individuals’ knowledge or consent. Data breaches are increasingly costly to companies and to affected users who must deal with the ensuing identity theft.

 

In 2018 the European Union implemented the General Data Protection Regulation, or GDPR. Despite its mild name, the GDPR had major consequences for individuals’ rights to control their data, and for companies that operate in the EU. Among other things, it gives the right to have personal data removed from a company’s records. This is the so-called “right to be forgotten”.

Gal Ringel is the Co-Founder and CEO of Mine, which allows users to identify which companies have their data, and it automates the process of removing data on behalf of its users. In this way, Mine aims to reduce online exposure and minimize risk for anyone using online services. Gal joins the show today to talk about his company, the impact of GDPR, and how his experience in military intelligence, venture capital, and tech led him to co-found the company.

Jordi Mon Companys is a product manager and marketer that specializes in software delivery, developer experience, cloud native and open source. He has developed his career at companies like GitLab, Weaveworks, Harness and other platform and devtool providers. His interests range from software supply chain security to open source innovation. You can reach out to him on Twitter at @jordimonpmm

Please click here to see the transcript of this episode. Sponsorship inquiries: [email protected]

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If you’re a sports fan and like to track sports statistics and results, you’ve probably heard of Sofascore. The website started in 2010 and ran on a modest single server. It now has 25 million monthly active users, covers 20 different sports, 11,000 leagues and tournaments, and is available in over 30 languages.

 

Josip Stuhli has been with Sofascore for 13 years. He started there as an engineer and is currently CTO. Josip joins the show today to talk about the challenges Sofascore encountered over the years, and how the team solved them. He discusses dealing with traffic spikes from game days, structuring and restructuring the codebase, organizing the frontend and backend, and much more.

Sean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from information visualization to quantum computing. Currently, Sean is Head of Marketing and Developer Relations at Skyflow and host of the podcast Partially Redacted, a podcast about privacy and security engineering. You can connect with Sean on Twitter @seanfalconer .

Please clicke here for the full transcript of this episode Sponsorship inquiries: [email protected]

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Cloud-based software development platforms such as GitHub Codespaces continue to grow in popularity. These platforms are attractive to enterprise organizations because they can be managed centrally with security controls. However, many, if not most, developers prefer a local IDE. Daytona is aiming to bridge that gap. It’s a layer between a local IDE and a backend server, so developers can work locally while interfacing invisibly with a remote environment. Ivan Burazin is the CEO and Co-Founder at Daytona, and he joins the show today to talk about how Daytona works, Spotify as an inspiration for his product, and more.

Jordi Mon Companys is a product manager and marketer that specializes in software delivery, developer experience, cloud native and open source. He has developed his career at companies like GitLab, Weaveworks, Harness and other platform and devtool providers. His interests range from software supply chain security to open source innovation. You can reach out to him on Twitter at @jordimonpmm

Please click here to see the transcript of this episode. Sponsorship inquiries: [email protected]

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Knowledge graphs are an intuitive way to define relationships between objects, events, situations, and concepts. Their ability to encode this information makes them an attractive database paradigm.

Hume is a graph-based analysis solution developed by GraphAware. It represents data as a network of interconnected entities and provides analysis capabilities to extract insights from the data. Luanne Misquitta is VP of Engineering at GraphAware and she joins the show today to talk about graph databases, and the engineering of Hume.

Starting her career as a software developer, Jocelyn Houle is now a Senior Director of Product Management at Securiti.ai, a unified data protection and governance platform. Before that, she was an Operating Partner at Capital One Ventures investing in data and AI startups. Jocelyn has been a founder of two startups and a full life cycle, technical product manager at large companies like Fannie Mae, Microsoft and Capital One.  Follow Jocelyn on LinkedIn  or Twitter @jocelynbyrne.

Please click here to view this show’s transcript.

Sponsorship inquiries: [email protected]

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Observability software helps teams to actively monitor and debug their systems, and these tools are increasingly vital in DevOps. However, it’s not uncommon for the volume of observability data to exceed the amount of actual business data. This creates two challenges – how to analyze the large stream of observability data, and how to keep down the compute and storage costs for that data.

Chronosphere is a popular observability platform that works by identifying the data that’s actually being used to power dashboards and metrics. It then shows the cost for each segment of data, and allows users to decide if a metric is worth that cost. In this way, technical teams can manage costs by dynamically adjusting which data is analyzed and stored. Martin Mao is the Co-founder and CEO of Chronosphere and he joins the podcast today to talk about the growing challenge of managing observability data, and the design of Chronosphere.

This episode is hosted by Lee Atchison. Lee Atchison is a software architect, author, and thought leader on cloud computing and application modernization. His best-selling book, Architecting for Scale (O’Reilly Media), is an essential resource for technical teams looking to maintain high availability and manage risk in their cloud environments. Lee is the host of his podcast, Modern Digital Business, an engaging and informative podcast produced for people looking to build and grow their digital business with the help of modern applications and processes developed for today’s fast-moving business environment. Listen at mdb.fm. Follow Lee at softwarearchitectureinsights.com, and see all his content at leeatchison.com. Please click here to see the transcript for this episode. Sponsorship inquiries: [email protected]

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